An Emerging Design Space of How Tools Support Collaborations in AI Design and Development

Developing AI/ML models and incorporating them into a product is complex work. While AI models are generally non-deterministic and have high capability uncertainty, the advent of foundation models further exacerbates the complexity of working with AI and ensuring responsible innovation. This complex work is achieved by not just AI practitioners, but through coordination and collaboration of different groups of practitioners, not all of whom might be experts in AI. Our primary objective is to explore how the tools and systems used by practitioners help achieve this complex work. To that end, we conducted a design space analysis of 18 relevant tools using corresponding research publications and constructed a design space with the dimensions - User, Axis of AI work, Semantics of Use, Tool Architecture, Artifact Type and Availability, and Collaboration Goals. Using these dimensions we derive four spirits of the tool in supporting collaborations - groupware, core practice & communication, community of practice, and visibility & bridging. Through this work, we contribute a conceptual design space of how tools can be designed to support collaborations in AI development and discuss how our design space can be leveraged by system designers and researchers working at the intersection of HCI, CSCW, and AI.